Download Artificial Intelligence

Artificial Intelligence
The Development
What is intelligence?
Written task:
– In your jotter write down your definition of
intellligence.
IQ Test
The basic idea behind the IQ test is that there
exists something called general intelligence
which can be quantified, at least relatively.
If an individual takes a properly designed
collection of tests, a single number can be
generated representing that person’s ‘intelligence
quotient’ or IQ. This number is normalised so that the average member
of the population has an IQ of 100. The distribution of the population
around the mean forms the so-called bell curve. Roughly 68% of the
population have an IQ between 85 and 115.
Put simply, your IQ is calculated based on the answers given to a host
of
‘intelligence testing’ questions and your score is compared to that of the
general population.
Critics of IQ tests believe that they are too restrictive and that it is not
possible to measure intelligence with a single number.
Computer Task
Go to the following website
– http://www.iqtest.dk
To take your IQ test
Intelligent Behaviours
Psychologists have struggled and argued
over this for years.
One approach is to examine behaviour
which we consider to be intelligent and
restrict our examination to that type of
behaviour.
This is called the behaviorist approach.
Intelligent Behaviours
We will restrict our behaviourist view of
intelligence to the following areas.
– the ability to communicate
– the ability to retain knowledge
– the ability to solve problems
The ability to communicate:
This means all sorts of communication, e.g.
speech, the written word and visual
communication, but the main factor is that the
person can express their ideas in a manner
which can be understood by others.
An example might be the ability to take part in a
debate putting forward a point of view and giving
good reasons for that point of view.
Another might be writing a book which captures
the imagination of its readers.
The ability to retain knowledge:
You will have come across this whenever
you have had to study for a test.
The more raw knowledge you possess the
larger the information base which you can
draw upon when trying to solve a problem.
The ability to solve problems:
You do this all the time in your
mathematics class when the tutor gives
out a whole stack of equations and leaves
you to work out the value of X or Y.
In fact being good at mathematics is seen
as a ‘sign of intelligence’ but we have had
enough definitions so we’re not going
there!
Written Task
In the grid below there are eight boxes and your
task is to place the digits 1–8 in each box but
consecutive numbers must not appear in boxes
which are touching (even at the corners). Do this
within 4 minutes and you are quite smart!
•No good, cannot place the 7
Artificial intelligence
Our perceptions of artificial intelligence tend
to be clouded by science fiction movies in
which machines ‘act’ like humans.
However, there is some value in the fact that
we instinctively compare the intelligence of
a machine to the intelligence of a human
because this is precisely the approach
which is taken in the scientific community.
Definitions of AI
– the study of how to build and/or program computers to enable them to
do the sorts of things that minds can do
– making computers do things that would require intelligence if done by
people
– the development of computers whose observable performance has
features which in humans we would attribute to mental processes
– the science of intelligence in general
– the intellectual core of cognitive science.
Note that most of these definitions make a direct comparison with
human intelligence.
We have discussed some attempts to define or measure intelligence.
However interesting these are, they do not provide much guidance to
people attempting to construct and verify machine intelligence.
Written Task
Complete Exercise 1 Question 1 - 6
The Turing Test
The interrogator is
connected to one person
and one machine via a
terminal, therefore can’t
see her counterparts.
Her task is to find out
which of the two
candidates is the
machine, and which is the
human only by asking
them questions.
If the machine can ‘fool’
the interrogator, it is
intelligent.
Computer Task
Go on to wikipedia.org.uk and look up the
Loebner Prize
What is it?
Why is the Turing Test important
to AI?
The Turing Test set a goal or challenge for
programmers in the field of AI.
The first person to create a program which
passes the Turing Test will enter the
history books and have a highly
commercially viable product.
Game playing
Early attempts to create artificial intelligence
were based on writing programs which could
play games.
It was felt that if a program could play a game
and possibly even beat a human, it would show
signs of intelligence.
Some of the games included noughts and
crosses, draughts and even chess.
These games (particularly chess) were viewed
as requiring a degree of logic, reasoning and
imagination
Practical Tasks
Pair up with a partner and play noughts
and crosses.
Game playing
All of the game-playing programs had
three characteristics in common: they
were played in a restricted environment;
they had a clearly defined set of rules,
and the criterion for success was
straightforward (i.e. someone wins).
This made programming games a lot
easier but the question still arises as to
whether it is really displaying intelligence.
Written Task
Complete Exercise 1 Questions 7 -10
Computer Task Exercise 1 Questions 1113
Natural language processing
(NLP)
The goal of natural language processing is to reach the position where
a human can talk to a computer, be understood and get a response
in the same way that they would from another human. We will
examine some of the attempts to create programs that could hold a
conversation with humans.
Language processing can be divided into two tasks:
1. Processing spoken language: involves taking words and
sentences inputted via a microphone and using the knowledge of
grammar and structure to interpret the input. Put simply, the user
‘converses’ with the machine.
2. Processing written text: handwriting is inputted via a stylus pen
(or scanned), the software attempts to make sense of the writing
and convert it to text as if typed.
Communication between man
and machine
Eliza
This was one of the first attempts to write a program which could hold a
conversation with a human.
The program consists of a knowledge base of facts, which we will
learn more about later. It was written by Joseph Weizenbaum in
1966 and, amazingly, is still popular today. The intention was to
create a ‘computer psychologist’ that could respond to people’s
problems by talking them through.
There are many Eliza spin-offs with different personalities, mainly
because people quite enjoy the novelty of having a conversation with a
computer.
Computer task
Go onto the following website;
Try a web-based version of Eliza at
http://www-ai.ijs.si/eliza/eliza.html
Limitations of Eliza
See definition sheet
Chatterbots
There has been a resurgence of interest in programs which can hold a
conversation with humans partly due to the expansion of the Internet.
Such programs are now commonly referred to as chatterbots or just
bots.
A chatterbot is a computer program for simulating conversation
between a human and a machine. You input a question or statement
of any kind, and the chatterbot replies, just as a person would (using
its own version of logic!).
Chatterbots try to create the illusion that an authentic exchange is
taking place between two thinking, living entities. Sometimes you
have to pinch yourself to remember that you are not talking to a real
person. At other times, it’s all too obvious.
A.L.I.C.E.
This bot is worth a special mention.
She is a more advanced program than
ELIZA because she has a larger
knowledge base (more facts stored)
Computer Task
Go to the following website:
http://www.pandorabots.com/pandora/talk?
botid=f5d922d97e345aa1
Applications of Chatterbots
There are three main applications of
chatterbots:
1. Internet search tools
2. Interactive website
3. Shopping bots
Internet search bots
Internet search engines work by employing
web ‘spiders’ which trawl the Internet and
add URL’s to a database which is then
searched by the user
‘Ask Jeeves’ is probably the most famous
search bot
Interactive website
Msn has a bot that you can hold a
‘conversation with’
Shopping bots
Shopping bots don’t really shop for the user,
but rather they engage in price
comparisons.
Written Task
Complete Exercise 2
Hardware Improvements
In the 1970s development of AI came to a halt
as the hardware and software of the time was
not powerful enough.
In the 1990s the processor speeds increased
dramatically as did the amount of RAM and
backing store.
Combined with a fresh approach to the
programming
All these factors contributed to the computers
running faster and storing more data.
Expert Systems
Expert systems use a different approach; they are a collection of
human know-how on one domain (One area of expertise) into a
knowledge-base.
A different problem, within the domain of the knowledge-base, can
be solved using the same program without reprogramming.
Instead of attempting to create an intelligent program, research
focused on creating a means of representing and accessing
knowledge.
The result was expert systems, computer programs which could
offer advice in a restricted subject where it was possible to create
facts and rules representing knowledge.
An expert system is an attempt to replace the human expert and to
make their knowledge available in a cost-effective and nonperishable form.
Advantages of Expert Systems
AVAILABILTIY
REDUCED WAGES/COST
COMBINED EXPERTISE
NON-PERMANENT
RELIABILITY
AVAILABILTIY
While human expert will need holidays,
lunch breaks and time off to rest a
computer does not.
Also in remote areas there is often a lack
of doctors for example but these towns
could access an expert system to help
diagnose an illness
REDUCED WAGES/COST
Human experts can command large fees
for their services, but once an expert
system is set up the company wage bill
can be reduced by employing fewer
people.
COMBINED EXPERTISE
A single human expert has only his own
knowledge gained from years of
experience to guide him when faced with a
problem.
An expert system can contain the
combined knowledge of many experts in
the same field.
NON-PERMANENT
Training a human expert can be very
expensive and they may change job or
retire or die.
RELIABILITY
Despite the best of intentions human
experts are prone to error.
Expert systems have a restricted domain;
they are only aware of the task for which
they were designed and are not prone to
interference from external factors.
This makes expert systems more reliable.
Further Applications
The commercial application of expert systems has grown
considerably over the years. Here are a few examples of uses:
• Medicine MYCIN was the first medical application of an expert
system. There are now systems which can give advice to doctors on
specialised areas such as kidney disease, cancer and blood
conditions.
• DHSS The laws and regulations governing the payment System
• Legal The laws in Scotland are vast and new laws are added each
year. By asking an expert system
solicitors can check that they are giving the right advice to a client.
(This is very controversial.)
• British Gas has an expert system which is used to calculate the
most likely place where corrosion will occur in a gas pipe.
• Power Stations During the 3 Mile Island accident, there were so
many alarms going off, and so many gauges to check that the
operators were confused.
Social, Legal and Ethical Issues
With the growth of AI systems it is becoming
increasingly lightly that computers will decide
which patient will be given a kidney transplant,
but is this moral.
Should you rely on a computer to diagnose a
fault on an aircraft.
Also billions of pounds have been spent by
governments on developing AI systems is this
morale when people in the world are dying of
starvation?
Effects of Employment
One of the advantages of expert systems for employers
is that of reduced cost due to the fact that we do not
require so many human experts.
Rather ironically, it was the lack of experts in the first
place that created the demand for expert systems; surely
we can’t have it both ways?
If we do not have any experts how do we check that the
expert system is doing a good job?
Creativity is seen as one aspect of intelligence but where
is the creativity when the expert system is simply
searching a database of knowledge? Where and how do
we create new ideas? It is the human experts that make
progress in their field by proposing theories and doing
hard research. Without human experts the body of
human knowledge will stagnate as new ideas are not
formulated.
Ethical Considerations
If the AI machine is programmed to diagnose
problems in a nuclear power station and
something goes wrong resulting in the loss of
human life who is to blame, the machine, the
manufacturer of the machine, the bosses of the
station, the programmer ???
The answer is
THE BOSSES OF THE STATION
Because you have to use information from the AI
program as you would when referencing a book.
Moral Issues
Is it right to give a machine the responsibility
of deciding whether a human being should
get an operation or whether a single
mother with 5 children should e given
extra benefits.
It is felt that computers are having a
dehumanising effect on man.
Written Task
Complete Exercise 3
Artificial Neural Systems
The most basic element of the
human brain is a specific type
of cell, which provides us with
the ability to remember, think,
and apply previous
experiences to our every
action.
These cells are known as
neurons, each of which may
connect with up to 200,000
other neurons and the power
of the brain comes from the
huge numbers of these basic
components and the multiple
connections between them.
Artificial Neural Systems
The brain consists of millions of
interconnected records. An artificial neural
system consists of hundreds of
interconnected artificial neurons, so it is
based on the same model as the human
brain, but with far fewer neurons.
Artificial Neural Systems
In contrast to conventional
computers, which are
programmed to perform a
specific task, neural networks
must be taught, or trained.
They can learn new
associations and new patterns
which, once learned, allow the
neural systems to recognise
features or characteristics,
e.g. learning to read English;
reading postcodes.
Artificial Neural Systems
An artificial neural system is an electronic
model of the brain consisting of many
interconnected single processors.
THIS IS FROM YOUR DEFFINITION
SHEET YOU MUST KNOW IT!!!
Applications of Artificial Neural
Systems
Artificial neural networks are best at identifying
patterns or trends in data, they are well suited to
prediction or forecasting needs including:
recognition of speakers in communications;
hand-written word recognition;
facial recognition (used by police forces).
Stock market prediction
Debt risk Assessment
Stock market prediction
Neural systems have been touted as allpowerful tools in stock-market prediction.
Some companies have claimed an
amazing 199.2% return over a two-year
period using their neural network
prediction methods.
Debit risk Assessment
Banks want to make as much money as
they can, and one way to do this is to
lower the failure rate by using neural
networks to decide whether the bank
should approve a loan.
The process works by analysing past
failures and making current decisions
based upon past experience.
Vision Systems
Making sense of the image is where the
neural system With its ability to patternmatch, the neural system will
characteristics of the object with those in
its memory the object. Without some form
of analysis of the object meaningful the
whole process would be pointless.
Applications of Vision Systems
Industrial Use
Military Use
Target Recognition
Industrial
There are a number of advantages that
machine vision systems have over people
for checking items on production lines.
First of all, a machine always does the
same thing, with the same accuracy, over
and over again, not being troubled with
fatigue or illness, not requiring any pause,
leisure time, holiday, or wages. So
machine vision brings:
Industrial
• consistency
• objectivity
• constant high
accuracy
• at low cost.
Written Task
Complete Exercise 5
Qu 3,5
Speech Recognition
The objective of speech recognition software
is to allow the user to communicate with
the computer by talking to it.
However, before using the system you must
first go through a training process; not for
you, for the computer!
Speech Recognition
This consists of reading a pre-defined text into
the computer for about twenty minutes. While
you are reading the text the computer is
sampling your voice and matching it to sounds
which are common in all words.
The reason everyone has to go through this
training process is because of the characteristics
of human speech. Everyone’s voice is unique
and so the computer has to be able to recognise
the individual patterns for each person.
Speech Recognition
The next stage is to dictate to the
computer through a microphone,
preferably when there is little noise in the
background that might distort the sound.
The quality of the microphone is important
and the computer’s processing power is
also a crucial factor.
Speech Recognition
Speech recognition uses a neural net to ‘learn’ to
recognise your voice.
As you speak, the voice recognition software remembers
the way you say each word. This customisation allows
speech recognition, even though everyone speaks with
different accents and inflection. In addition to learning
how you pronounce words speech recognition also uses
grammatical context and frequency of use to predict the
word you wish to input.
These powerful statistical tools allow the software to cut
down the massive language database before you even
speak the next word.
Further Uses
Telephony and telecommunications
Embedded and network-based speech recognition
technology is used by a number of companies in the
industry. Embedded voice recognition enhances
handsets’ capabilities, making them more productive,
multitasking tools.
Wireless phones, wireline phones, PDAs and other devices
can include many speech features, such as voice
activation and voice dialling. Voice portals use networkbased speech recognition to help operators perform a
range of transactions and access information more
efficiently.
Note
Speech Recognition Systems need to be
training to recognised the users voice.
Factors that effect the accuracy of speech
recognition
– Background noise
– Accents
– Colds
Handwriting Recognition
In the early systems you would need to train a
handwriting recognition system, e.g. a palm top.
Now no training is necessary, it is no possible to
write on the LCD screen and have the input
converted to text while you are still writing.
The processor speed will be a large factor when it
come to the time delay between writing and the
transcribed text appearing, but normally within a
few seconds.
Computer task
http://www.penreader.com/WinCE/PenRead
er.html
http://www.thomastannahill.com/tomato/applet.html
Accuracy
As with voice recognition, accuracy depends on
the user being consistent.
Here are a few recommendations from the
manufacturer to improve accuracy:
You will have the best recognition quality when
using the default letter shape settings.
Try to write bigger
Upper case characters should be at least twice
as big a lower case characters
Applications
Handheld devices which use handwriting
recognition include:
• PDA (Personal Digital Assistant)
• Tablet PC (mentioned above)
• Electricity meter reading (take the
customer’s signature as well)
• Post office form filling
• Supermarkets for stock control.
Written Task
Exersice 7
Qu 1,4,5,6,8 and 9
Robots
What do you think a robot looks like?
What can they Do?
This is not the case, one of the most
commonly used robots in industry is the
arm.
The anatomy of a ROBOT
Wrist
Roll
Wrist
pitch
Elbow
Shoulder
Base
The anatomy of a ROBOT
Each of the joints allows the robot to move
on different planes and enables it to
position its end effectors to perform tasks.
The wrist is similar to a human wrist and can
be designed with a wide range of motion.
This enable the robot to reach into places
that would be difficult or impossible to
reach by a human arm.
The anatomy of a ROBOT
This type of flexibility makes the robot’s value
much greater and its capabilities attractive. The
grippers are at the end of the wrist.
They are used to hold whatever the robot is to
manipulate.
Some robots have end-of-arm tools instead of
grippers. A few examples of these tools are
painters, arc welders and spot welders. All these
put together make a manipulator.
This enables a robot to pick up an object,
manipulate it, and set it down where desired.
Robot Sensors
A robot can use a wide range of switches. First is
a manual switch which tells the robot yes or no.
Virtually all manual switches are electric and
most often are used to turn the robot on and off
or to make adjustments to the automotive cycle.
Limit Switches are activated by levers, toggles,
push buttons, plungers, rollers, whiskers and just
about anything else the developer can engineer
to make the device automated.
Robot Sensors
Proximity switches do not require physical
contact or light radiation to feel or sense
an object. They are called proximity
switches because they are able to sense a
nearby object without actually touching it.
This gives the robot the ability to do
something that humans are not able to do,
and is done by using electromagnetic
waves or sonar.
Robot Sensors
Photoelectric sensors are sensitive to light
radiation.
Sometimes it is useful to detect electromagnetic
radiation outside the visible range.
This is where infrared is used. This would include
the sensing of hot objects, as hot objects emit
infrared rays. These are highly useful for
machine malfunctions and are used as
automatic emergency shutoffs.
Commonly Used Sensors
• bump (contact) sensors (switches see
above)
• proximity switch
• light sensors/photoelectric (see above)
• temperature sensors
• pressure sensors.
Basics
As you might have noticed an intelligent
robot is not a carbon copy of Robo cop but
rather a robot with a sensor e.g. a robot on
a car manufacturing plant which sprays
the car, that has a proximity sensor to
sense when humans are about so that
they do not spray them with paint or a lift
door that does not crush humans (touch
sensor).
Advantages of robots
Increased productivity:
– Robots do not require breaks or even working hours; they can be
put into production continuously day and night.
Improved accuracy:
– The precisely controlled actions of a robot mean that in
situations where detailed work is required they are more
accurate than humans, e.g. checking circuit boards.
Consistency:
– The first job of the day and the last will be done in exactly the
same way with no loss of quality. A human can get tired and
make mistakes.
Reduced wage bill:
– With fewer staff employed and no wages for the robots this is an
area of major cost savings.
Advantages of robots
Hostile environment:
– Here spray painting by a robot has many advantages.
One of them is removing humans from the exposure
to fumes. Many of the paints and coatings that are
used contain harmful gases that are toxic to the
human body.
– Off-shore oil production is conducted in an extremely
hostile environment where robots are used to check
rig platforms and weld joints.
Applications of robots
The vast majority of intelligent robots are
used in manufacturing industries.
In 1992 there were 800,000 industrial
robots on the planet and this figure is
estimate to rise to more than 1 million by
2004.
Other uses are often related to working in
remote or hostile environments.
Applications of robots
Welding
– The main reason robots are used extensively in
industrial welding is their productivity rate. On
average robotic welders perform at the same rate as
fifteen humans. This is due to the human need to
adjust helmets, gas levels, and other safety
equipment that robots do not need. Another benefit of
using robots is that a skilled one can operate two to
three robotic welders at one time. Besides the faster
speed being achieved by robots the superior quality
of the weld is easily visible.
Applications of robots
Assembling
– Robots are used to assemble watches, calculators,
printers, circuit boards, electric motors, alternators
and countless other products. They can be
programmed to assemble anything that can be
broken down into simple step-by-step instructions.
The main problem with using a robot for assembly is
in product design. Many older products were not
designed to be assembled by a robot, so until they
are redesigned, assembly will not be completely
robotic. This is why an enormous amount of time is
being spent in the research and development of
everyday products that can be assembled by robots.
Other applictions include;
–
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–
–
–
–
–
–
–
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Military/police use
Unmanned Aircraft
Medicine
Pipe Inspection
Bomb Disposal
Land-mine Detection
Automated Mail Delivery
Factory Mobile Robot
Mars Explorer
Vacuum Robot
Land-mower Robot (Mowbot)
Intelligent Robots
All of the robots above have sensors and are involved in
some sort of decision-making process. The fact that they
all have sensors and a feedback mechanism is without
doubt an improvement over the ‘dumb’ robots of the
past, but are they ‘intelligent’?
Remember our three criteria of intelligence are the ability
to:
1. communicate
2. retain knowledge
3. solve problems.
These robots satisfy some of the criteria to a limited
extent, but few of them can truly be described as
intelligent. Most of them are simply using an imperative
program which responds to the input from the sensor
and takes appropriate action.
Intelligent Robots
An intelligent robot employs some aspect of
artificial intelligence. For example, it could be
equipped with:
– a vision system which can interpret images and then
make a response;
– an artificial neural system which gives it the ability to
learn;
– speech recognition which is able to respond to verbal
commands.
Techniques like these are increasingly being
applied to robots in all of the fields described in
the previous section. This makes these robots
more flexible and adaptable.
Search Techniques
A knowledge base is a special kind of database for
knowledge management. It provides the means for the
computerized collection, organization, and retrieval of
knowledge.
Machine-readable knowledge bases store knowledge
in a computer-readable form, usually for the purpose of
having automated querying applied to them. They
contain a set of data, often in the form of rules that
describe the knowledge in a logically consistent manner.
Some machine-readable knowledge bases are used with
artificial intelligence, for example as part of an expert
system that focuses on a domain like prescription drugs
or customs law.
Search Techniques
Imagine a knowledge base for finding a fault in a
car. A dialogue between the computer and the
user might proceed as follows:
Computer Does the engine turn when you engage the
ignition?
User No.
Computer When you put the lights on do they go dim?
User Yes.
Computer When you turn the ignition is there a clicking
sound?
User Yes.
Computer The starter motor in your car has jammed.
Search Techniques
You can see that there is a decision-making
process going on here and each question
depends on the answer to the previous question.
This type of process can be represented as a
branching tree, more commonly called a search
tree.
Many problems can be represented by a search
tree. Various search techniques can be used to
find the solution to the problem
Search Techniques
The search techniques apply to a search tree which contains all the
different permutations or choices possible when starting from one
state and trying to reach a ‘goal’ state. This might make a little more
sense if we consider the following example.
We are faced with a number puzzle which contains the numbered
tiles 1 to 5. In the initial state, the tiles are not in the correct order.
Our objective or ‘goal state’ is to move the numbered tiles around
the block so that the tiles read 1 to 5 in the correct order.
It is possible to construct a search tree to address this problem.
Practical Task
Use a sheet of paper provided, and cut it in to 6
pieces.
Write the numbers 1 – 5 and leave 1 blank
Start with initial state and find you goal state, you
can move 1 space at a time, draw moves into
your jotter.
Search Techniques
Search Techniques
Two search techniques are commonly used
in these situations:
1. breadth first
2. depth first.
Breadth First
This is where the tree is searched from left
to right working its way down layer by
layer until the goal state is found. (D)
Breadth First Advantage
The advantages of breadth-first searching
are that the shallowest solution will be
found first, i.e. the one nearest the top of
the tree.
If the goal state was at F then the path
taken would be P→I→R→F. Because it is
near the top it was found quickly.
Depth First
This is where the tree is searched from
top to bottom working its way across
Branches until the goal state is found. (D)
Depth First Advantage
If the goal state is located far down the
leftmost branch then depth-first search
would reach the goal before breadth-first.
Chess
Consider how a chess player decides which move to
make next. He does not calculate every path because he
knows that some are clearly bad and will give him a poor
or lost position.
From past experience he can choose a path for the first
several moves which he knows are good as he has
played them before or some other top players have used
them.
Such strategies are referred to as ‘book moves’ in the
world of chess as the paths have already been played at
some point by grandmasters or other top players and are
recorded in textbooks.
What the chess player is really doing here is choosing a
path down the search tree which he believes will lead
him to his goal, to win.
Written Task
Exercise 9